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Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling

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Abstract

In this paper, we examine corporate insolvency in the Gulf Cooperation Council (GCC) region between 2004 and 2011. Data comprises 28 financial ratio variables from 112 firms. We use Logit regression with best-subset selection criteria to investigate the predictive value of the ratios in the GCC context, particularly cash flow-based ratios. We also examine the main dimensions of the ratios, and the weights firms attach to them, using 3-way Multidimensional Scaling (MDS). We find that a parsimonious Logit model with the profitability ratio EBITTL, the leverage ratio TLTA and the cash flow ratios CFFOTA and CFFOCL can predict insolvency, ex-ante, with 84.8, 95.6 and 73.9 % overall, type I and II accuracy, respectively. From MDS, we uncover four financial-ratio dimensions: (i) ‘Non-strategic sales activities’, (ii) ‘Profitability and financial stability balance’, (iii) ‘Sales activities against capital conversion’; and (iv) ‘Market value against cash generation’. Insolvent firms appear very specific and attach most salience to the ‘Non-strategic sales activities’ dimension, unlike solvent firms which attach more salience to the other three dimensions. Therefore, the results imply that, to reduce susceptibility to insolvency in the GCC, managers should focus less on non-strategic sales activities.

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Acknowledgments

I would like to thank anonymous reviewers for their helpful comments.

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Authors and Affiliations

  1. School of Management, University of Southampton, Highfield, Southampton, SO17 1BJ, UK

    Layla Khoja, Maxwell Chipulu & Ranadeva Jayasekera

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  1. Layla Khoja
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  2. Maxwell Chipulu
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Correspondence to Layla Khoja.

Appendices

Appendix 1

See Table 10.

Table 10 Sample of insolvent and solvent firms
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Appendix 2: Logit prediction model results

See Fig. 4, Tables 11 and 12.

Fig. 4
figure 4

ROC curve for logit prediction model

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Table 11 Prediction logit model fit and parameter estimates
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Table 12 Classification matrix of logit prediction model
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Appendix 3: Probit prediction model results

See Fig. 5, Tables 13 and 14.

Fig. 5
figure 5

ROC curve for probit prediction model

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Table 13 Prediction probit model fit and parameter estimates
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Table 14 Classification matrix of logit prediction model
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Appendix 4

See Table 15.

Table 15 Significance of financial ratios across insolvency studies
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Khoja, L., Chipulu, M. & Jayasekera, R. Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling. Rev Quant Finan Acc 46, 483–518 (2016). https://doi.org/10.1007/s11156-014-0476-y

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